The present specification relates to image processing and color correction.
It is conventional for an image processing application to provide tools with which a user can correct distortions of colors in a digital color image. A digital color image, by way of example, can be a scanned picture, a frame of a video clip, or a photo taken with a digital camera.
The colors in a digital image may be distorted for many reasons. There may be a color cast arising from surrounding elements in the scene, such as a green cast from surrounding vegetation. Any ambient lighting that differs significantly from normal daylight conditions can potentially impart an unwanted color change. An image taken at sunset or sunrise, for example, may impart an unwanted reddish-orange cast. Many cameras modify the image to compensate for such situations, either by letting the user manually specify a lighting condition or by attempting to correct this automatically by balancing color components across all or a portion of the image. Both methods can fail: the user may select the wrong setting; the image may have a predominant color component that defeats the automatic algorithm; or there may be more than one dominant light color in the scene.
There are conventional tools that adjust a color balance in a digital image to correct for color distortions.
One conventional tool allows user manipulation of one or more color curves of an image to adjust color balance. A red channel, a green channel, and a blue channel of the image, for example, can each have curves or values that a user adjusts to effect color correction. Such a conventional tool is typically used to adjust the entire image according to the new color balance based on the user's overall perception of the image.
Another conventional tool that can be used to correct color distortions allows a user to adjust color balance by changing an apparent illuminant color temperature in an image. In the example of a direct sunlight photo, the image can be adjusted to make the color temperature of the image cooler. As a result, however, pixels that should appear to be white may become bluish. In the example of an indoor photo, an adjustment to make the color temperature warmer may cause white pixels to appear red.
Many photographers have rules of thumb for how to go about adjusting skin color. Such rules require a subjective judgment and leave room for uncertainty. An example would be to use a curves tool in an image processing program such as the Adobe® Photoshop® program to modify each color component separately in order to obtain a specified ratio of red to blue and red to green components in the skin. An example description for CMYK images is: “Skin tones in a Caucasian person should consist of roughly equal parts of magenta and yellow, and a dash of cyan (equal to 15-25% the value of the magenta and yellow). Darker skinned people will have more cyan, and lighter skinned people will have less. Oriental people will have little cyan, and a smidgen more yellow than magenta.”